Natural language understanding

An intent is what a customer is actually trying to do, inferred from what they wrote or said rather than from the specific words used. Two very different messages can share an intent, which is why routing and automation are built on intent rather than on keyword matching.

Entity extraction is the process of pulling structured values — an order number, an IBAN, a product name, a date — out of a customer’s free-text message. Reliable extraction is what allows an automated agent to act inside a business system rather than only classify the request.

Conversational AI describes systems that understand and respond in natural language across chat, email, and voice. The category spans intent-based bots and modern language-model agents, and the practical difference between them is whether the system can only reply or can also take action in business systems.

An utterance is a single thing a customer said, exactly as the model receives it, before any cleaning or interpretation. Utterances are the raw material for intent classification and evaluation sets, and preserving them verbatim is what allows AI errors to be reproduced and diagnosed later.